Visual Analytics Approach to Comprehensive Meteorological Time-Series Analysis
Abstract
:1. Introduction
1.1. Background
1.2. Overview
2. Data Sources
3. Methods
3.1. Data Import
3.2. Data Structure and Quality Check
3.3. Data Diversity, Pattern Search, and Anomaly Detection
3.4. Communicating Insights and Findings
4. Results and Discussion
4.1. Advantages of Visual Analytics Approach over Traditional Descriptive Methods
4.2. Comprehensive Analysis of Meteorological Time Series
4.2.1. Completeness Check and Anomaly Detection
4.2.2. Data Diversity and Pattern Search
Annual Analysis
Seasonal Analysis
Hot and Cold Events
5. Supporting Case Study
6. Future Development Prospects
7. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Data Attribute | Missing [%] | Min. | Max. | Mean | Standard Deviation | Coeff. of Variation | |
---|---|---|---|---|---|---|---|
API 1 | T | 0.05 | −8.0 | 36.6 | 12.5 | 8.38 | 0.67 |
RH | 0.05 | 19 | 100 | 69 | 17.2 | 0.25 | |
WS | 0.05 | 0 | 3.72 | 0.96 | 0.61 | 0.63 | |
WD | 54 | 0 | 360 | - | 102.25 | 0.48 | |
TMY 2 | T | 0.05 | −18.3 | 31.7 | 9.9 | 8.76 | 0.88 |
RH | 0.05 | 24 | 100 | 72 | 16.94 | 0.24 | |
WS | 0.05 | 0 | 9.13 | 1.97 | 1.28 | 0.65 | |
WD | 0.05 | 0 | 360 | - | 97.93 | 0.47 |
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Vuckovic, M.; Schmidt, J. Visual Analytics Approach to Comprehensive Meteorological Time-Series Analysis. Data 2020, 5, 94. https://doi.org/10.3390/data5040094
Vuckovic M, Schmidt J. Visual Analytics Approach to Comprehensive Meteorological Time-Series Analysis. Data. 2020; 5(4):94. https://doi.org/10.3390/data5040094
Chicago/Turabian StyleVuckovic, Milena, and Johanna Schmidt. 2020. "Visual Analytics Approach to Comprehensive Meteorological Time-Series Analysis" Data 5, no. 4: 94. https://doi.org/10.3390/data5040094